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Material Selection Methods: A Review

  • M. B. BabanliEmail author
  • F. Prima
  • P. Vermaut
  • L. D. Demchenko
  • A. N. Titenko
  • S. S. Huseynov
  • R. J. Hajiyev
  • V. M. Huseynov
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 896)

Abstract

Material selection is an important problem attracting theoretical and practical interest. Nowadays, a lot of materials and alloys are designed. In most alloys some properties are good and in compliance with the requirements, but some of them are not acceptable. Generally, for material selection methods it is necessary to have unique synergy of theoretical knowledge and practical experiences data. Scientists used and developed some selection methods due to all of these.

Keywords

Material selection method Multi-criteria decision making (MCDM) Fuzzy approach methods Z-number 

References

  1. 1.
    Frang, M.: Quantitative Methods of Material Selection. Handbook of Material Selection (2002)Google Scholar
  2. 2.
    Ashby, M.: Materials Selection in Mechanical Design. Butterworth-Heinemann, Oxford (2010)Google Scholar
  3. 3.
    Cebon, D., Ashby, M.: Data systems for optimal material selection. Adv. Mat. Process. 161(6), 51–54 (2003)Google Scholar
  4. 4.
    Jahan, A., Edwards, K.L.: Multi-criteria Decision Analysis for Supporting the Selection of Engineering Materials in Product Design. Butterworth-Heinemann, Oxford (2016)Google Scholar
  5. 5.
    Ashby, M.: Multi-objective optimization in material design and selection. Acta Materilia 48, 359–369 (2000)CrossRefGoogle Scholar
  6. 6.
    Jahan, A., Ismail, M.Y., Sapuan, S.M., Mustapha, F.: Material screening and choosing methods – a review. Mater. Des. 31, 696–705 (2010)CrossRefGoogle Scholar
  7. 7.
    Cavallini, C., Giorgetti, A., Citti, P., Nicolaie, F.: Integral aided method for material selection based on quality function deployment and comprehensive VIKOR algorithm. Mater. Des. 47, 27–34 (2013)CrossRefGoogle Scholar
  8. 8.
    Zafarani, H.R., Hassani, A., Bagherpour, E.: Achieving a desirable combination of strength and workability in Al/SiC composites by AHP selection method. J. Alloy. Compd. 589, 295–300 (2014)CrossRefGoogle Scholar
  9. 9.
    Shimin, V.V., Shah, V.A., Lokhande, M.M.: Material selection for semiconductor switching devices in electric vehicles using Analytic Hierarchy Process (AHP) method. In: IEEE International Conference on Intelligent Control and Energy Systems (ICPEICES) (2016)Google Scholar
  10. 10.
    Kiong, S.C., et al.: Decision making with the Analytical Hierarchy Process (AHP) for material selection in screw manufacturing for minimizing environmental impacts. Appl. Mech. Mater. 315, 57–62 (2013)CrossRefGoogle Scholar
  11. 11.
    Athawale, V.M., Chakraborty, S.: Material selection using multi-criteria decision-making methods: a comparative study. In: Proceedings of Institution of Mechanical Engineers, Part L, vol. 226, no. 4, pp. 267–286 (2012). Journal of Materials: Design and ApplicationsCrossRefGoogle Scholar
  12. 12.
    Flywheels move from steam age technology to Formula 1: Jon Stewart (2012)Google Scholar
  13. 13.
    Jee, D.-H., Kang, K.-J.: A method for optimal material selection aided with decision making theory. Mater. Des. 21(3), 199–206 (2000)CrossRefGoogle Scholar
  14. 14.
    Rai, D., Jha, G.K., Chatterjee, P., Chakraborty, S.: Material selection in manufacturing environment using compromise ranking and regret theory-based compromise ranking methods: a comparative study. Univ. J. Mater. Sci. 1(2), 69–77 (2013)Google Scholar
  15. 15.
    Chatterjee, P., Chakraborty, S.: Material selection using preferential ranking methods. Mater. Des. 35, 384–393 (2012)CrossRefGoogle Scholar
  16. 16.
    Jahan, A., Bahraminasab, M., Edwards, K.L.: A target-based normalization technique for materials selection. Mater. Des. 35, 647–654 (2012)CrossRefGoogle Scholar
  17. 17.
    Kl, E.: Selecting materials for optimum use in engineering components. Mater. Des. 26, 469–474 (2005)CrossRefGoogle Scholar
  18. 18.
    Fayazbakhsh, K., Abedian, A., Manshadi, B.D., Khabbaz, R.S.: Introducing a novel method for materials selection in mechanical design using Z-transformation in statistics for normalization of material properties. Mater. Des. 30, 4396–4404 (2009)CrossRefGoogle Scholar
  19. 19.
    Chatterjee, P., Athawale, V.M., Chakraborty, S.: Materials selection using complex proportional assessment and evaluation of mixed data methods. Mater. Des. 32, 851–860 (2011)CrossRefGoogle Scholar
  20. 20.
    Milani, A.S., Shanian, A., Madoliat, R., Nemes, J.A.: The effect of normalization norms in multiple attribute decision making methods: a case study in gear material selection. Struct. Multidisc. Optim. 29, 312–318 (2005)CrossRefGoogle Scholar
  21. 21.
    Jeya Girubha, R., Vinodh, S.: Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Mater. Des. 37, 478–486 (2012)CrossRefGoogle Scholar
  22. 22.
    Ahn, K.K., Kha, N.B.: Modeling and control of shape memory alloy actuators using Preisach model, genetic algorithm and fuzzy logic. Mechatronics 18, 141–152 (2008)CrossRefGoogle Scholar
  23. 23.
    Xue, Y.-X., You, J.-X., Lai, X.-D., Liu, H.-C.: An interval-valued intuitionistic fuzzy MABAC approach for materialselection with incomplete weight information. Appl. Soft Comput. 38, 703–713 (2016)CrossRefGoogle Scholar
  24. 24.
    Gul, M., Celik, E., Gumus, A.T., Guneri, A.F.: A fuzzy logic based PROMETHEE method for material selection problems. Beni-Suef Univ. J. Basic Appl. Sci. 7, 68–79 (2018)CrossRefGoogle Scholar
  25. 25.
    Zhu, X.F.: A web-based advisory system for process and material selection in concurrent product design for a manufacturing environment. Adv. Manuf. Technol. 25, 233–243 (2005)CrossRefGoogle Scholar
  26. 26.
    Welling, D.A.: A fuzzy logic material selection methodology for renewable ocean energy applications by proquest, Umi Dissertation Publishing (2011)Google Scholar
  27. 27.
    Zadeh, L.A.: A note on Z-numbers. Inf. Sci. 181, 2923–2932 (2011)CrossRefGoogle Scholar
  28. 28.
    Babanli, M.B., Huseynov, V.M.: Z-number-based alloy selection problem. In: 12th International Conference on Application of Fuzzy Systems and Soft Computing, ICAFS 2016, Vienna, Austria, vol. 102, pp. 183–189 (2016). Procedia Computer ScienceCrossRefGoogle Scholar
  29. 29.
    Jahan, A., Ismail, M.Y., Shuib, S., Norfazidah, D., Edwards, K.L.: An aggregation technique for optimal decision-making in materials selection. Mater. Des. 32, 4918–4924 (2011)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • M. B. Babanli
    • 1
    Email author
  • F. Prima
    • 2
  • P. Vermaut
    • 2
  • L. D. Demchenko
    • 3
  • A. N. Titenko
    • 4
  • S. S. Huseynov
    • 1
  • R. J. Hajiyev
    • 1
  • V. M. Huseynov
    • 1
  1. 1.Azerbaijan State Oil and Industry UniversityBakuAzerbaijan
  2. 2.Chimie ParisTech, UMR CNRS 7045ParisFrance
  3. 3.National Technical University of Ukraine “KPI”KievUkraine
  4. 4.Institute of Magnetism under NAS and MES of UkraineKievUkraine

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